I think you all know that correspondent banks are required to meet specific regulatory obligations while maintaining their correspondent relationships, as well as meet general compliance obligations to report suspicious activity, prevent money laundering, and comply with economic sanctions. A mouthful but true, nonetheless. Although the Legacy AML and traditional AI systems, in place at banks monitor customer activity, this approach is not effective for monitoring flow of funds that aren’t related to the bank’s own customers. Moreover, these systems are based on rules that incorporate preset scenarios with conditions and thresholds looking for patterns that are known. We do it differently. Our IntuitiveAI for correspondent banking analyzes SWIFT messages without setting any predefined condition or threshold. Historical data is used to learn what is “normal” in terms of transactions and data flow and then detect anomalous activity with respect to that normal. This approach enables complex patterns of behavior to be caught which otherwise would have been missed by legacy or traditional AI systems. At the core of the solution is the data scientist It’s up to them to set the analysis strategy. The strategy includes selecting the relevant data sources and calculation of “features” — the key parameters and ways of deriving information specifically relevant for correspondent banking. ThetaRay’s IntuitiveAI algorithm then analyzes these features altogether to define what’s normal and what’s abnormal activity, without setting any predefined patterns or thresholds. The key data sources utilized are the SWIFT messages (MT103, 202, 202C), KYC information, Country Risk and bank risk information. These data sources are extracted over a historical period of a few years and are then utilized to calculate an entity called the “Full Path.” The Full Path covers the end-to-end payment flow and banks participating in the payment. Once the Full Path is derived from the SWIFT messages, several features are calculated. The features designed are related to volume and value changes in the Full Path activity over time, various combinations of risk indicators of the sources and destinations of funds, banks involved and the structure and location of the bank codes in the path. Stay with me now. An example of such a feature is the total amount of SWIFT 103 messages that have been sent over a Full Path during a specific time period and with a specific currency. We then take that total amount and compare it to similar time frames in the past in a form of a statistical calculation. Then, this calculation is factored with another calculation which indicates how significant this total amount is compared to other similar paths during the same time period. These two calculations are then combined into a single feature value. Several of these smart features are calculated and then injected altogether into the algorithms. Still here? Once features are created, an analysis is conducted and fine-tuned. Results worthy of further investigation are turned over to analysts to then take that investigation forward. On top of all this we have to ensure that we do what

My banker told me that, in theory, managing his relationship with regulators and respondent banks is straightforward. Then he paused and said, “Actually, about as straightforward as explaining quantum physics to a five-year old.” And he’s right. Both understanding quantum physics and correspondent banking relationship obligations are tough. Quantum Physics makes sense of the smallest things in nature – how the billions of sub-atomic particles work together. Correspondent banks need to make sense of even the smallest transactions in a financial network and work together with their respondent banks to reduce financial crime risks. Quantum physics tries to prove there is ‘weirdness’ at the subatomic level which indicates the existence of multiple universes. Correspondent banks have to prove they are complying with both multiple universes of regulations, as well as its own risk management obligations. In Quantum physics reality is complex, not fixed and shifting. For Correspondent banks the reality is that maintaining an effective anti-financial crime (AFC) program entails complexity and commitment to address shifting financial crime vectors and proactive engagement along the entire correspondent banking network. Dealing with the above challenges requires significant effort, both for AFC experts and rocket scientists (but that’s a longer discussion). Correspondent banks need relationships with respondent banks that make their lives easier not more difficult – they don’t create additional enforcement risks and they minimize compliance burdens. Getting comfortable with a respondent bank’s AFC program means having as complete an understanding of their AFC program as you do your own. You have to do the hard work. • Assess the risk of the respondent bank’s business and operating strategy • Develop a governance structure providing for appropriate escalation as necessary • Escalation paths need to be staffed by experienced, well-trained and engaged professionals • Develop a compliance culture • Ensure regular, thorough, and independent reviews and internal audits of the AFC program Both rocket science and AFC are critical to the world. Rocket scientists drive innovations which lay the groundwork for our future. AFC experts secure the world so we can take advantage of that future. And if you do want to explain quantum physics to a five-year old, try quantum physics for kids. Webinar: Avoiding the Correspondent Banking Hurt locker To learn more, join our upcoming webinar on how to avoid the Correspondent Banking Hurt Locker by identifying unknown threats Click here for more information and registration

Correspondent banking is like jamming your big toe on a door jam. It hurts but you still have to keep moving. Banks continue to have highly visible and damaging correspondent banking failures but they still have to deal with cross-border payments, whether they have the financial crime controls in place or not. It was so bad during the early 2000’s that banks were caught with their hands in the till – hiding originating banks in order to avoid sanctions. They’re right to be concerned, scared, worried – pick your favorite anxiety-laden word. Regulatory expectations and global standards, as published by the FATF for example, categorize correspondent banking as high risk and should be addressed with strictest of controls. Meanwhile, it remains a safe haven for money launderers, those financing terrorism, human traffickers and other bad actors. Banks like windows! They want full transparency when it comes to customer activity, but when it comes to correspondent banking, the windows are small and dirty. Originating banks must rely on third party banks and their AML controls. Criminals take advantage of the bank’s weak legacy systems and lack of standards. They can easily find the weak spots in the system, open faulty accounts and move around their dirty money. Although a bit more challenging, criminals are able to legitimize their transactions by opening destination accounts. In so doing, they can mask high volume funds flowing into an account, in a way that the bank will not suspect anything egregious. Since KYC isn’t monitored, and is isolated from global payments, the chances a bank will catch this suspicious activity is slim to none. And since this multi-station banking is inherently difficult to secure, it makes it easier for the bad guys. Things sound grim don’t they? Well maybe, BUT legacy techniques, legacy AI is notoriously poor at dealing with a bank’s entire transaction flow. Our IntuitiveAI algorithms can easily see each and every connection within the entire network of banks which are part of every transaction they conduct. It uncovers both the risks and safe havens to easily recognize laundromats. Thetaray for Correspondent banking covers the entire correspondent banking workflow. Webinar: Avoiding the Correspondent Banking Hurt locker To learn more, join our upcoming webinar on how to avoid the Correspondent Banking Hurt Locker by identifying unknown threats Click here for more information and registration